Triple
T17102710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SLIM |
E415017
|
entity |
| Predicate | landingObjective |
P64674
|
FINISHED |
| Object | land near a specific small target area |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: land near a specific small target area | Statement: [SLIM, landingObjective, land near a specific small target area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landingObjective Context triple: [SLIM, landingObjective, land near a specific small target area]
-
A.
landing
Indicates the action or event of an entity coming down from the air or a higher position to make controlled contact with a surface.
-
B.
campaignObjectiveSpanish
Indicates the specific goal or purpose of a campaign as expressed in the Spanish language.
-
C.
campaignObjectivePersian
Indicates the specific goal or intended outcome of a campaign, expressed in the Persian language.
-
D.
aimOf
chosen
Indicates that one entity serves as the goal, purpose, or intended target of another entity’s action, plan, or existence.
-
E.
landingPrecisionGoal
Indicates the intended level of accuracy or closeness with which a landing is planned to reach its target location.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2495c88190b5b16a006a994faf |
completed | April 18, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69e35d6b1b988190a8d6b6fe78c35e59 |
completed | April 18, 2026, 10:31 a.m. |
Created at: April 10, 2026, 5:35 a.m.